A class of non-linear exposure-response models suitable for health impact assessment applicable to large cohort studies of ambient air pollution

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  • dc.contributor.author Nasari, Masoud M.
  • dc.contributor.author Szyszkowicz, Mieczysław
  • dc.contributor.author Chen, Hong
  • dc.contributor.author Crouse, Daniel L.
  • dc.contributor.author Turner, Michelle C.
  • dc.contributor.author Jerrett, Michael
  • dc.contributor.author Pope III, C. Arden
  • dc.contributor.author Hubbell, Bryan
  • dc.contributor.author Fann, Neal
  • dc.contributor.author Cohen, Aaron
  • dc.contributor.author Gapstur, Susan M.
  • dc.contributor.author Diver, W. Ryan
  • dc.contributor.author Stieb, David
  • dc.contributor.author Forouzanfar, Mohammad H.
  • dc.contributor.author Kim, Sun-Young
  • dc.contributor.author Olives, Casey
  • dc.contributor.author Krewski, Daniel
  • dc.contributor.author Burnett, Richard T.
  • dc.date.accessioned 2024-03-26T07:15:36Z
  • dc.date.available 2024-03-26T07:15:36Z
  • dc.date.issued 2016
  • dc.description.abstract The effectiveness of regulatory actions designed to improve air quality is often assessed by predicting changes in public health resulting from their implementation. Risk of premature mortality from long-term exposure to ambient air pollution is the single most important contributor to such assessments and is estimated from observational studies generally assuming a log-linear, no-threshold association between ambient concentrations and death. There has been only limited assessment of this assumption in part because of a lack of methods to estimate the shape of the exposure-response function in very large study populations. In this paper, we propose a new class of variable coefficient risk functions capable of capturing a variety of potentially non-linear associations which are suitable for health impact assessment. We construct the class by defining transformations of concentration as the product of either a linear or log-linear function of concentration multiplied by a logistic weighting function. These risk functions can be estimated using hazard regression survival models with currently available computer software and can accommodate large population-based cohorts which are increasingly being used for this purpose. We illustrate our modeling approach with two large cohort studies of long-term concentrations of ambient air pollution and mortality: the American Cancer Society Cancer Prevention Study II (CPS II) cohort and the Canadian Census Health and Environment Cohort (CanCHEC). We then estimate the number of deaths attributable to changes in fine particulate matter concentrations over the 2000 to 2010 time period in both Canada and the USA using both linear and non-linear hazard function models.
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Nasari MM, Szyszkowicz M, Chen H, Crouse D, Turner MC, Jerrett M, et al. A class of non-linear exposure-response models suitable for health impact assessment applicable to large cohort studies of ambient air pollution. Air Qual Atmos Health. 2016 Dec;9(8):961-72. DOI: 10.1007/s11869-016-0398-z
  • dc.identifier.doi http://dx.doi.org/10.1007/s11869-016-0398-z
  • dc.identifier.uri http://hdl.handle.net/10230/59571
  • dc.language.iso eng
  • dc.publisher Springer
  • dc.relation.ispartof Air Quality, Atmosphere & Health . 2016 Dec;9(8):961-72
  • dc.rights This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri http://creativecommons.org/licenses/by/4.0/
  • dc.subject.keyword Air pollution
  • dc.subject.keyword Cohort
  • dc.subject.keyword Exposure
  • dc.subject.keyword Mortality
  • dc.subject.keyword Particulate matter
  • dc.title A class of non-linear exposure-response models suitable for health impact assessment applicable to large cohort studies of ambient air pollution
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion

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